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Computational models of stochastic variability in the auditory nerve and electromyography recordings induced by transcranial magnetic stimulation /

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dc.contributor.authorMoezzi, Bahar,
dc.contributor.schoolUniversity of South Australia. School of Information Technology and Mathematical Sciences.
dc.contributor.schoolSchool of Information Technology and Mathematical Sciences.
dc.date.issued2017
dc.description1 ethesis (xxii, 120 pages) :
dc.descriptionillustrations
dc.descriptionIncludes bibliographical references (pages 103-118)
dc.description.abstractNervous systems are extraordinarily complex. This complexity gives rise to their ability to sense and process information and survive in the world. The down side of this complexity is that many disorders such as Alzheimer’s disease, multiple sclerosis, depression,schizophrenia, stroke and problems with hearing and vision can arise. One of the techniques used in studying both healthy and diseased nervous systems is computational modeling (Dayan and Abbott; 2001). In this thesis, we have studied two topics in which computational modeling may help in the treatment or diagnosis of neural disorders and for understanding their underlying causes.
dc.description.dissertationThesis (PhD(Computer and Information Science))--University of South Australia, 2017.
dc.identifier.urihttps://hdl.handle.net/11541.2/128518
dc.language.isoen
dc.provenanceCopyright 2016 Bahar Moezzi.
dc.subject.lcshAcoustic nerve.
dc.subject.lcshAuditory pathways.
dc.subject.lcshCochlear implants
dc.titleComputational models of stochastic variability in the auditory nerve and electromyography recordings induced by transcranial magnetic stimulation /
dc.typethesis
dcterms.accessRights506 0#$fstar $2Unrestricted online access
ror.fileinfo12149282680001831 13149282670001831 Moezzi, Bahar - Thesis_Redacted
ror.mmsid9916158007501831

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